Application of Shuffled Frog-Leaping Algorithm to Reduce Energy Consumption in Cloud Data Centers by Optimizing Scheduling Management and Virtual Machines Consolidation

Today, green cloud computing has been concerned due to the reduction of environmental impacts. One of the criteria that has been emphasized in green cloud computing is energy consumption of data centers. One way to reduce energy consumption, which we is emphasized in this paper, is tasks scheduling management and consolidation of virtual machines. In this paper, an algorithm is presented to manage both tasks scheduling and load balancing. This algorithm, called the Shuffled Frog-Leaping provides a significant improvement against other existing models in terms of energy consumption and migration of virtual machines using memory, collaboration and sharing information among frogs, high convergence speed and better flexibility against local optimum problem. In this paper, the dynamic resource management is based on the consolidation of virtual machines and is implemented according to service level agreement by the proposed method. The difference between this method and other existing methods is that it shows improvement of time, speed and accuracy of convergence parameters. Experimental results show that the proposed method outperforms existing ones in terms of energy consumption, number of virtual machine migrations and service level agreement violation.